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Code Repair Generation Combo

Community
ArabelaTso
code-repair-generation-combo

Automatically repair buggy code and generate comprehensive tests for Python, Java, and C++ programs. Use when users need to fix logic errors or runtime errors in functions, modules, or repositories. Accepts specifications via natural language descriptions, existing test cases, or input/output examples. Generates corrected code, creates or updates tests to verify correctness and prevent regressions, and produces a detailed report explaining the bug, fix, and testing strategy. Triggers on requests like "fix this bug", "repair this code", "debug this function", or "this code is broken".

Overview

PublisherArabelaTso
RepositorySkills-4-SE
Skill namecode-repair-generation-combo
Stars
258
Forks
25
Bundled files
4
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ArabelaTso on GitHub. Read the source before you install it.

Installation

Install the Code Repair Generation Combo AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ArabelaTso/Skills-4-SE/tree/main/skills/code-repair-generation-combo
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ArabelaTso/Skills-4-SE.git /tmp/Skills-4-SE
mkdir -p .claude/skills
cp -r /tmp/Skills-4-SE/skills/code-repair-generation-combo .claude/skills/code-repair-generation-combo
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Code Repair Generation Combo in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Code Repair Generation Combo on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Code Repair Generation Combo is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Code Repair + Generation Combo

Automatically diagnose and repair buggy code while generating comprehensive tests to verify correctness and prevent regressions.

Workflow

Follow this systematic approach for bug fixing and test generation:

1. Understand the Bug

Read the buggy code - Use Read tool to examine the problematic code thoroughly.

Analyze the specification - Understand expected behavior from:

  • Natural language description from user
  • Existing failing test cases
  • Input/output examples provided
  • Error messages or stack traces

Identify the scope - Determine if the bug affects:

  • A single function
  • Multiple related functions
  • An entire module
  • Cross-module interactions

2. Diagnose the Root Cause

Trace the logic - Walk through the code execution mentally or with examples.

Identify the bug type:

  • Logic error: Code runs but produces wrong results (off-by-one, wrong operator, incorrect condition)
  • Runtime error: Code crashes or throws exceptions (null pointer, array out of bounds, type mismatch)

Pinpoint the exact location - Identify the specific lines causing the issue.

Understand side effects - Check if the bug affects other parts of the codebase.

3. Fix the Code

Apply minimal changes - Fix only what's broken, preserve existing functionality.

Use Edit tool - Make precise changes to the buggy code.

Verify the fix logic - Ensure the fix addresses the root cause, not just symptoms.

Preserve code style - Match existing formatting, naming conventions, and patterns.

4. Generate Comprehensive Tests

Load testing patterns - Read the appropriate reference file:

  • Python: references/python-testing.md
  • Java: references/java-testing.md
  • C++: references/cpp-testing.md

Create test cases covering:

  • Normal cases: Typical valid inputs
  • Edge cases: Boundary values, empty inputs, single elements
  • Error cases: Invalid inputs, null values, exceptions
  • Regression cases: Specific inputs that triggered the original bug

Update existing tests if they exist, or create new test files following language conventions.

Use parametrized tests when testing multiple similar cases.

5. Verify and Run Tests

Execute the tests - Use Bash tool to run the test suite:

  • Python: pytest test_file.py -v
  • Java: mvn test or gradle test
  • C++: ./test_executable or ctest

Ensure all tests pass - If tests fail, revisit the fix.

Check coverage - Verify that the fix and related code paths are tested.

6. Generate Bug Fix Report

Use the report template - Read assets/bug-fix-report-template.md and populate it with:

  • Summary of the bug and fix
  • Root cause analysis
  • Changes made with file paths and line numbers
  • Test coverage details
  • Verification of regression safety

Be specific and clear - Include code snippets, test results, and reasoning.

Example Usage

Example 1: Python logic error

User: "This factorial function returns 24 instead of 120 for input 5. Fix it."

1. Read the buggy code
2. Identify: off-by-one error in loop range
3. Fix: Change `range(1, n)` to `range(1, n+1)`
4. Generate tests covering 0, 1, 5, negative numbers
5. Run pytest and verify all pass
6. Generate report

Example 2: Java runtime error

User: "My sorting method throws NullPointerException with null elements."

1. Read the code and identify null comparison issue
2. Fix: Add null checks before comparisons
3. Generate JUnit tests for arrays with nulls, empty arrays, normal cases
4. Run tests and verify
5. Generate report

Example 3: C++ logic error with examples

User: "Binary search returns -1 for existing elements. For [1,3,5,7,9] and target 5, should return 2."

1. Read code and trace with provided example
2. Identify: incorrect mid calculation or boundary condition
3. Fix the bug
4. Generate Google Test cases with provided example and additional edge cases
5. Compile and run tests
6. Generate report

Language-Specific Notes

Python:

  • Use pytest framework
  • Follow PEP 8 style
  • Use type hints if present in original code

Java:

  • Use JUnit 5 framework
  • Follow Java naming conventions
  • Handle null safety explicitly

C++:

  • Use Google Test or Catch2
  • Check for memory leaks with valgrind if applicable
  • Handle pointer safety and bounds checking

Resources

references/ - Testing patterns and best practices for each language assets/ - Bug fix report template for consistent documentation

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Code Repair Generation Combo AI skill do?

Automatically repair buggy code and generate comprehensive tests for Python, Java, and C++ programs. Use when users need to fix logic errors or runtime errors in functions, modules, or repositories. Accepts specifications via natural language descriptions, existing test cases, or input/output examples. Generates corrected code, creates or updates tests to verify correctness and prevent regressions, and produces a detailed report explaining the bug, fix, and testing strategy. Triggers on requests like "fix this bug", "repair this code", "debug this function", or "this code is broken".

Why use Code Repair Generation Combo on TypingMind?

Because you install it once and use it with any model. Code Repair Generation Combo is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Code Repair Generation Combo in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ArabelaTso/Skills-4-SE/tree/main/skills/code-repair-generation-combo. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Code Repair Generation Combo?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Code Repair Generation Combo?

As many as you like. As long as a model supports skills, you can use Code Repair Generation Combo with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Code Repair Generation Combo AI skill free?

Yes. It is published on GitHub by ArabelaTso under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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